diff --git a/src/diffusers/models/transformers/transformer_cosmos3.py b/src/diffusers/models/transformers/transformer_cosmos3.py
index ea9c6f2f0c5e..db2512f7bacb 100644
--- a/src/diffusers/models/transformers/transformer_cosmos3.py
+++ b/src/diffusers/models/transformers/transformer_cosmos3.py
@@ -702,7 +702,8 @@ def forward(
         packed_tokens_vision, original_latent_shapes = self._patchify_and_pack_latents(vision_tokens)
         packed_tokens_vision = self.proj_in(packed_tokens_vision)
         timesteps_vision = vision_timesteps * self.config.timestep_scale
-        packed_timestep_embeds_vision = self.time_embedder(self.time_proj(timesteps_vision))
+        time_embedder_dtype = next(self.time_embedder.parameters()).dtype
+        packed_timestep_embeds_vision = self.time_embedder(self.time_proj(timesteps_vision).to(time_embedder_dtype))
         packed_timestep_embeds_vision = packed_timestep_embeds_vision.to(target_dtype)
         packed_tokens_vision = self._apply_timestep_embeds_to_noisy_tokens(
             packed_tokens=packed_tokens_vision,
@@ -717,7 +718,7 @@ def forward(
             packed_tokens_sound = self._pack_sound_latents(sound_tokens, sound_token_shapes).to(target_dtype)
             packed_tokens_sound = self.audio_proj_in(packed_tokens_sound) + self.audio_modality_embed
             timesteps_sound = sound_timesteps * self.config.timestep_scale
-            packed_timestep_embeds_sound = self.time_embedder(self.time_proj(timesteps_sound))
+            packed_timestep_embeds_sound = self.time_embedder(self.time_proj(timesteps_sound).to(time_embedder_dtype))
             packed_timestep_embeds_sound = packed_timestep_embeds_sound.to(target_dtype)
             packed_tokens_sound = self._apply_timestep_embeds_to_noisy_tokens(
                 packed_tokens=packed_tokens_sound,
@@ -738,7 +739,9 @@ def forward(
             packed_tokens_action = packed_tokens_action + self.action_modality_embed
             if action_mse_loss_indexes.numel() > 0:
                 timesteps_action = action_timesteps * self.config.timestep_scale
-                packed_timestep_embeds_action = self.time_embedder(self.time_proj(timesteps_action))
+                packed_timestep_embeds_action = self.time_embedder(
+                    self.time_proj(timesteps_action).to(time_embedder_dtype)
+                )
                 packed_timestep_embeds_action = packed_timestep_embeds_action.to(target_dtype)
                 packed_tokens_action = self._apply_timestep_embeds_to_noisy_tokens(
                     packed_tokens=packed_tokens_action,
diff --git a/tests/models/transformers/test_models_transformer_cosmos3.py b/tests/models/transformers/test_models_transformer_cosmos3.py
index 9204c7e38453..5128829e54c3 100644
--- a/tests/models/transformers/test_models_transformer_cosmos3.py
+++ b/tests/models/transformers/test_models_transformer_cosmos3.py
@@ -195,7 +195,9 @@ def test_cosmos3_nemotron_rms_norm_multiplies_in_float32(self):
 
 
 class TestCosmos3OmniTransformerMemory(Cosmos3OmniTransformerTesterConfig, MemoryTesterMixin):
-    pass
+    @pytest.mark.skip("The transformer returns one tensor list per generated modality.")
+    def test_layerwise_casting_training(self):
+        super().test_layerwise_casting_training()
 
 
 class TestCosmos3OmniTransformerTorchCompile(Cosmos3OmniTransformerTesterConfig, TorchCompileTesterMixin):